Semi-autonomous Active Safety Systems

J. Karl Hedrick

About the Event

Over the past few decades, intelligent vehicle systems have become
increasingly important in their contribution to vehicle safety. A
semi-autonomous system that explicitly models the driver’s behavior is
able to make accurate assumptions on the predicted safety of the
driver. Rather than disconnecting the driver from the vehicle, our
approach incorporates the driver using a model predictive control
method to predict the future trajectories of the closed-loop
driver-vehicle system. We can then add the minimal corrective action
necessary to keep the driver from violating safety constraints. The
successful implementation of this controller, however, is predicated
on a reliable approximation of the environment and the vehicle's
inertial properties. A system that can account for these variations
can execute more accurate control. In addition, it is useful to model
the interaction between the tires and the road to correctly predict
the vehicle’s trajectory. Although most contemporary vehicle systems
compute the control inputs based on a fixed tire-road friction
coefficient, real-time estimation is vital for improvement of the
performance of vehicle control systems. Use of in-tire accelerometers
allows us to classify the road surface conditions with direct
measurement from the tire. This integrated approach, combining
accurate inertial parameter estimates, real-time estimation of
tire-road adhesion, and a control system that explicitly models driver
behavior, allows the development of a new echelon of driver assistance
systems.

Biography

J. Karl Hedrick is the James Marshall Wells Professor of Mechanical Engineering at the University of California (UC) at Berkeley. He received his BS degree (1966) from the University of Michigan, and his MS (1970) and PhD (1971) degrees from Stanford University. His research focuses on the application of advanced control theory to a wide variety of vehicle dynamic systems including automotive, aircraft and ocean vehicles. He is currently the Director of Berkeley’s Vehicle Dynamics Laboratory and has served as the Director of the UC PATH Research Center (1997-2003). He has received numerous awards, including 2006 ASME Rufus Oldenburger Medal, ASME JDSMC Best Paper Award (1983&2001), IEEE TCST Outstanding Paper Award (1998), the AACC O. Hugo Schuck Best Paper Award (2003) and gave the Nyquist Lecture at the ASME 2009 DSCC.